🌐 Google Search Trends Analysis using Pytrends
This project analyzes public interest in key tech topics like Cloud Computing, Data Science, and Machine Learning using Google Trends data via the pytrends API.
📌 Project Objectives Use the Pytrends library to access Google Trends data programmatically
Compare search interest over time for multiple tech-related keywords
Visualize trends to discover insights into public interest and demand
🛠️ Technologies & Libraries Used Python
Pytrends (Unofficial Google Trends API)
Pandas
Matplotlib / Seaborn (for visualization, if used)
Jupyter Notebook
📊 Features 🔍 Build keyword payloads dynamically
🕒 Analyze search trends over a custom time frame (today 12-m)
🌍 Filter by country or region (optional)
📈 Generate trend line plots for comparative analysis
📥 How to Run Clone the repo
bash Copy Edit git clone https://github.com/yourusername/Google-Search-Analysis.git cd Google-Search-Analysis Install requirements
bash Copy Edit pip install pytrends pandas matplotlib Open the notebook
bash Copy Edit jupyter notebook Google-Search-Analysis.ipynb 📎 Example Output (You can insert a screenshot of a trend plot here)
🔚 Conclusion This project is a simple yet effective way to leverage Google's public search data to gain insights on technological trends. It's great for analysts, data scientists, and tech enthusiasts.